Hawary00/VAE-MNIST
PyTorch implementation of a Variational Autoencoder (VAE) trained on MNIST to learn and generate handwritten digits, including both standard VAE ( fully connected (vanilla) VAE) and convolutional VAE (ConvVAE) variants with visualization and interpolation tools.
Stars
2
Forks
1
Language
Python
License
—
Category
Last pushed
Nov 13, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/Hawary00/VAE-MNIST"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
jxhe/vae-lagging-encoder
PyTorch implementation of "Lagging Inference Networks and Posterior Collapse in Variational...
chaitanya100100/VAE-for-Image-Generation
Implemented Variational Autoencoder generative model in Keras for image generation and its...
taldatech/soft-intro-vae-pytorch
[CVPR 2021 Oral] Official PyTorch implementation of Soft-IntroVAE from the paper "Soft-IntroVAE:...
lavinal712/AutoencoderKL
Train Your VAE: A VAE Training and Finetuning Script for SD/FLUX
Rayhane-mamah/Efficient-VDVAE
Official Pytorch and JAX implementation of "Efficient-VDVAE: Less is more"